Quick Update
Thu, Sep 1st 2016 4:01a Niklas HeidloffSome people have asked why I haven’t blogged since June. Here is why …
Almost two years ago I started to work for IBM Emerging Technologies. I wanted to work in this group for multiple reasons. One reason was because some of the people in that group worked as developer evangelists for Bluemix which is what I wanted to do as well. I really enjoyed this role since I could learn a lot, since I could blog and open source samples, since I could attend developer conferences and more. As yo

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Analyzing Data with IBM Watson Internet of Things
Tue, Jun 14th 2016 4:47a Niklas HeidloffOnce you’ve connected your ‘things’ with the Watson Internet of Things platform, the next question is how to process the received data. In some scenarios the raw data triggers actions immediately, sometimes the data needs to be persisted so that it can be used for historical/descriptive analysis and sometimes the data is used to perform predictive analytics and prescriptive analytics.
The Watson Internet of Things platform uses MQTT which is a lightweight and secure publish/sub

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Recognizing Text in Images with Watson’s Visual Recognition API
Mon, Jun 6th 2016 6:23a Niklas HeidloffThe Watson Visual Recognition service is now generally available and a lot of new functionality has been added. The service combines the old beta capabilities plus the Alchemy functionality and the previous Visual Insights service.
With the new service you can receive classifications of images, faces can be detected and even text is recognized. All of this can be done by simply invoking APIs without requiring deep learning skills.
With the new service you can now define and train multiple custom

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Pictures from Bluemix at DNUG
Fri, Jun 3rd 2016 4:12a Niklas HeidloffThis week I attended DNUG in Hamburg/Germany. DNUG is the German user group for IBM Collaboration Solutions. In the app dev track several sessions covered Bluemix.
It was the 43th conference of DNUG but this time it was very different. After years of declining numbers of attendees the new board has managed to double the number of attendees compared to the last conference. The new DNUG organization is now much leaner and cost effective. One example is that all servers and infrastructure has been

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Machine Learning Courses for Developers
Wed, Jun 1st 2016 3:07a Niklas HeidloffAs readers of my blog will know, I want to learn more about machine learning. I’ve managed to run some samples and I’ve built my own first little samples. It feels like the next step is to understand more about the different algorithms, for example when to pick which one and how to tune the parameters to achieve the best results.
To learn more, I’ve started to watch the first hours of the awesome courses below. The courses are a great introduction to machine learning and very d

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Spark Machine Learning Samples for IBM Bluemix
Mon, May 30th 2016 4:54a Niklas HeidloffBelow is a quick overview of samples that demonstrate how to use the machine learning capabilities in Spark on IBM Bluemix.
Flight Delay Predictions
David Taieb posted the slides of his hands-on session how to predict flight delays based on historical data and whether predictions. The sample uses the machine learning algorithms Logistic Regression, Random Forrest, Decision Tree and Naive Bayes.
Open Article
Rock-Paper-Scissors Game
When playing rock-paper-scissor everyone has his/her own strat

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Integrating Tools in Bluemix DevOps via Open Toolchain
Fri, May 27th 2016 5:26a Niklas HeidloffAt InterConnect IBM previewed a new set of DevOps functionality which is now available as experimental on Bluemix. Via Toolchains IBM tools and third party tools can be used seamlessly together for the development, deployment and management of Bluemix applications.
With toolchains other common non-IBM tools can be integrated nicely in the Bluemix developer experience, for example by providing a single sign on between Bluemix and the various tools. Additionally the tools can interact between each

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Running the Spark Recommendations Sample on Bluemix
Wed, May 25th 2016 5:29a Niklas HeidloffApache Spark comes with a set of machine learning samples. One of those sample is a movie recommendation system which makes personalized recommendations based on a technique called Collaborative Filtering. In this article I describe on a high level how this sample works.
For more details check out the tutorial from the Berkeley university. The dataset used in that tutorial contains 10 million ratings from 72,000 users on 10,000 movies. The Spark project comes with a synthetic dataset in the same

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Discovering Open Data via Analytics Exchange on Bluemix
Wed, May 25th 2016 3:22a Niklas HeidloffAs I’m trying to learn more about machine learning I spent some time to look for data that I can use. While GitHub is the place to get open source code, there doesn’t seem to be a counterpart for open data. Below are a couple of websites that help finding data.
In Bluemix there is an Analytics Exchange which gives you access to free and open data in categories such as economy and business, leisure, transportation, and others. The screenshot shows a sample dataset which contains revie

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Getting started with Spark Machine Learning on Bluemix
Thu, May 19th 2016 6:15a Niklas HeidloffI’m fascinated by the power of machine learning and I’m trying to learn more about this technology. I’ve started to look into how to use the machine learning library in Spark.
The Spark documentation of the spark.ml package explains the main concepts like pipelines and transformers pretty well. There are also a number of good videos on YouTube about machine learning. I’ve used the spark.ml library as opposed to spark.mllib since it’s the recommended approach and it